- Health-focused AI startups are raising billions to help improve the U.S. system.
- AI can help streamline clinical documentation, drug discovery, and medical billing.
- This article is part of “Trends in Healthcare,” a series on the innovations and industry leaders shaping patient care.
The founder of Suki, a startup that uses artificial intelligence to automate healthcare documents, raised $70 million from investors in a Series D funding round that was disclosed last fall.
He added that it didn’t take much convincing: with an epidemic of stressed and burned-out doctors, there was a clear need for their AI software, he added.
“Most of the conversations with investors over the last year and a half have been, ‘Well, it looks like the market is there,'” said Punit Singh Soni, founder of Suki. “Are you going to be the winner or not?”
Suki sells an AI-powered assistant that takes notes during a conversation between patients and clinicians. Notes can be reviewed by the doctor and submitted as an electronic health record. This saves time on administrative tasks and gives doctors more time to care for patients, an increasingly limited resource among healthcare professionals.
Investigations have always revealed that doctors and other medical workers are exhausted to work in a system that is often overloaded, convoluted and inefficient. The United States spent $4.8 trillion on healthcare in 2023, study finds. January report from the Peter G. Peterson Foundation. The United States also spends more per person than almost all other developed countries, according to a report by the Organization for Economic Cooperation and Development. Despite this, health outcomes were worse, with Americans facing lower life expectancy, higher rates of treatable and preventable excess deaths, and less effective health care systems.
Cash-strapped hospitals and private practices lag behind the financial services and telecommunications sectors in applying new technologies, but the healthcare sector is increasingly considering artificial intelligence as it faces high labor costs and ample opportunities to automate routine tasks. The pandemic has exacerbated these challenges due to staff shortages as overworked doctors and nurses have left the profession.
To make healthcare more efficient, AI startups like Suki, Zephyr AI and Tennr have raised millions with broad promises, including making repetitive tasks like billing and note-taking easier, improving accuracy clinical diagnosis and identifying the right patient population for emerging needs. treatments.
But the challenges are vast. Healthcare sector budget allocations for generative AI are behind those of many other basic industriessuch as energy and materials, consumer goods and retail. Clinical diagnosis will continue to require the presence of a human being, so the process cannot be fully automated. The healthcare industry is highly regulated, and often venture capitalists wait for the federal government to clarify the laws before aggressively advancing AI technological advancements.
A $370 billion bet to increase health sector productivity
Consulting firm McKinsey believes that generative AI can increase productivity in the healthcare, pharmaceutical and medical products industries. up to $370 billion by accelerating drug research, facilitating clinical documentation, expediting medical billing, and helping doctors make diagnoses.
Some major fundraising rounds announced in 2024 highlight the various use cases of AI in the healthcare sector. They include $150 million raised by clinical documentation AI startup Abridge in February, drug discovery AI startup Xaira Therapeutics which raised $1 billion ahead of its April launch, $33 million Series B dollars from Atropos Health in May to help doctors analyze real-world evidence. with generative AI, and medical billing automation provider Candid Health raised $29 million in September.
Parth Desai, partner at Flare Capital Partners, has led investments in healthcare startups such as Photon Health and SmarterDx. He said healthcare organizations have been spending more money on strengthening their AI strategies, starting in late 2022 and continuing through 2024. This is driving demand for the tools these startups are developing. There’s also less pressure to immediately prove a return on investment, which budget-conscious health systems have closely monitored in the past when allocating dollars to technology.
“The thing we really look at before making an investment decision is: Are there budgets today to fund this technology?” Desai told Business Insider. “Or are they going to exist in a big enough way in the next five to 10 years to support this technology?”
Frank health and Akasa aim to reduce costs and automate medical billing
One particularly promising area is medical billing, which could benefit from large-scale automation of language models. An LLM could, for example, analyze a large volume of claims in a client’s system and accurately match them to insurers’ unique billing codes, a process required for reimbursing a physician for his or her services. Hospitals have traditionally relied on human medical coders to seek reimbursement from insurers.
“The software used to do billing was built a long time ago and was basically not kept up to date,” said Nick Perry, co-founder and CEO of Candid Health.
Malinka Walaliyadde, CEO of Akasa – another AI startup focused on medical billing – said the company builds custom LLMs for each healthcare facility it serves. Typically, the goal of these LLMs is to reduce costs by reducing the reliance on human medical coders. This often reduces billing errors and speeds up reimbursement cycles.
“We looked at what the main problems in health systems are,” Walaliyadde told BI. He said Akasa’s goal was to develop LLM products for medical coding and simplify prior authorization, a process that requires approval from a healthcare provider before a patient can receive treatment. “These are the ones where you can really make a difference,” Walaliyadde said.
AI for health exams
George Tomeski, the founder of Helfie AI, is pitching investors to raise up to $200 million in a new funding round that he hopes to close by the first half of 2025.
Tomeski said the funding would help Helfie scale as it moves out of beta testing for the company’s app. The app, also called Helfie, uses a smartphone’s camera to perform medical “checks” to detect diseases such as COVID-19, tuberculosis and certain skin conditions.
“We target all health conditions that lead to preventable mortality,” Tomeski said, adding that the app focuses on respiratory and cardiovascular problems. The intention is that these checks – which can cost as little as $0.20 per person per screen – serve as a form of preventative care and an incentive to go see a doctor in person.
While some of the funding goes toward sales and marketing, talent acquisition, and compliance with privacy and health data regulations, a large portion is still allocated to product development as the AI technology is advancing rapidly.
Dr. Brigham Hyde, co-founder and CEO of Atropos Health, said its latest funding announcement, in May, was timed to coincide with the launch of ChatRWD, an AI co-pilot capable of answering doctors’ questions and producing publications quickly. studies based on health data. Hyde said he wanted to bring in big partners this time, including pharmaceutical giant Merck and medical supplies and equipment maker McKesson.
But Hyde also had to show some restraint. He said that when Atropos Health launched its Series B rounds, dozens of venture capitalists expressed interest in leading the round. The company was offered up to $100 million, but only accepted a third of that amount.
“I don’t always think it’s a good idea,” Hyde told BI. “As a founder, you want to raise the right amount of money for your business and where you are at.”
It can be tempting to take on more, like many healthcare AI startups – the vast majority still in development seed and startup funding rounds – race to outwit their rivals. Even if the technology is suitable, it must move past regulatory approvals and convince cautious hospitals and health systems to open their wallets.
“You can create as many products as you want, but you can never create a market,” said Soni of Suki. “It appears, or it doesn’t appear.”